Individual tree detection in large-scale urban environments using high-resolution multispectral imagery

Jonathan Ventura, Camille Pawlak, Milo Honsberger, Cameron Gonsalves, Julian Rice, Natalie L. R. Love, Skyler Han, Viet Nguyen, Keilana Sugano, Jacqueline Doremus, G. Andrew Fricker, Jenn Yost, Matt Ritter

Abstract: Highlights•We perform a comparative study of tree detection methods in urban environments.•We introduce a new dataset of over 1,500 images and almost 100,000 tree annotations.•Our novel neural network regression approach outperformed previous methods.•We applied our method to produce a complete map of the urban forest of California.